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EAD Factory MCP Server

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evidence_group_update_bulk

Update multiple evidence groups in one call by supplying each group ID and the metadata changes. Batch-edit evidence group metadata efficiently without repeated single-group calls.

Instructions

Updates the editable metadata of SEVERAL evidence groups in one call (each entry carries its own evidenceGroupId and changes). Prefer evidence_group_update for a single group. Requires: the evidenceGroupIds to update (evidence_group_search to find them).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsYes
patchNo
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnlyHint=false and destructiveHint=false, so the agent knows it's a non-read-only, non-destructive write. However, the description does not disclose bulk operation behavior such as atomicity, partial failure handling, or error semantics. The statement 'each entry carries its own evidenceGroupId and changes' conflicts with the actual schema (flat ids array), adding confusion rather than clarity.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded with the core action and scope. However, the sentence 'each entry carries its own evidenceGroupId and changes' is misleading and inaccurate given the schema, occupying space that could be better used for clarifying the request structure.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a bulk update tool with patch semantics and no output schema, the description is incomplete. It omits how to structure the patch array, the relationship between ids and patch, error handling, and partial-failure behavior. The mismatch between the described 'per entry' model and the actual schema further undermines completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must fully explain parameters, but it barely does. It mentions 'evidenceGroupIds' and 'changes' without mapping to the actual schema properties 'ids' and 'patch'. It never explains the patch operations (REPLACE, REMOVE), path/value structure, or how patch applies to the multiple ids, and the 'each entry' phrasing actively misleads.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool updates editable metadata of several evidence groups in one call, using a specific verb and resource. It also explicitly differentiates from the sibling tool evidence_group_update by advising to prefer that for a single group.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides explicit usage guidance: 'Prefer evidence_group_update for a single group' and notes the prerequisite to find evidenceGroupIds via evidence_group_search. This clearly indicates when to use the bulk tool versus the single-update alternative.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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